Preparation, Validation and Registration of HP CDM Project. S.D.Sharma MCT Participant -HP

Transcription

1 Preparation, Validation and Registration of HP CDM Project S.D.Sharma MCT Participant -HP

2 Title- India: Himachal Pradesh Reforestation Project- Improving Livelihoods and Watersheds Registration No. : 4174 (CDM Registry) Reforestation Project Salient Features Expected Operational Life time : 60 Years Crediting period Project proponent Project Partners : 20 years (Renewable twice) : Government of HP : Govt. of H.P, World Bank, Govt. of Spain

3 Salient Features Contd.---- Area : 4003 ha GPs : 177 Parcels : 420 Size of parcels : 1 to 150 ha Land status: degraded forest /community /private Methodology : AR-ACM-001 (Version.03) Carbon Pool Selected: 3 (AGB+BGB+SOC) Native and local Species Carbon Revenue to go to communities as incentive to protect Forests/ Watersheds.

4 CDM proposal preparation process CDM methodology is very complex: Selection of Methodology according to UN procedure ARAM004: Honduras ARAM002: Moldova ARACM001: Consolidated Intensive filed studies on land availability in 177 panchayats Studies on vegetation (forest, grassland & farm land), soil organic carbon, grazing, procuring and interpreting satellite imageries FSI Delineation of 420 Land parcels using GPS coordinates Household surveys consultations with communities (committees constituted under HP PFM Rules,2001)

5 Challenges faced.. Defining the project boundary -Each discrete parcel of land should have a unique geographical identification with the boundary clearly defined for each discrete parcel. -very time consuming and expensive task -requires technical expertise Demonstrating land eligibility: -past history, satellite imagery, processing (FSI). Establishing baseline: -time consuming, technical know how needed. Demonstrating additionality : -Barrier analysis: Transparent documentation required for different questions or criteria at the scale of the project. -Records difficult to access and procure. -Impossible to justify from all perspectives as required- institutional, financial, social, and technical, etc.

6 Challenges faced.. Estimating leakage: -Difficult to estimate and quantify the pressure on land parcels included for the project area. - Communities dependent on multiple land parcels for grazing and fuelwood extraction purposes. - Multiple stakeholders dependent on land parcels. -Shift of pressure is difficult to identify and quantify given the dependence of communities on multiple land parcels and multiple community groups dependent on identified land parcels. Calculation of CERs: -Growth rate data for species growing under agro-forestry systems and private plantations limited. -Data for increment on species grown on degraded land categories limited -Baseline growth rate: Unavailable

7 Project Boundary and Land Eligibility Cluster of Multiple Discrete Parcels of land Remote Sensing Data - GPs with significant quantities of eligible lands shortlisted (FSI data/survey maps). Communities sensitized, PRA conducted to identify Spareable/agreed land parcels likely to qualify. GPS Survey - Generate Boundaries/polygans, measure area. FSI analysis for eligibility using Satellite Data (TM) and current (LIS-III). Generated output on maps. Scrutiny by Validation Team Onsite Visit / Satellite Data

8 Eligibility criteria Tree crown cover value of 15% Land area not less than 0.05 hectare Tree height of 2 meters and above

9 1989 LANDSAT TM 2004 IRS P6 LISS III

10 NM 060-P1

11 SPREAD OF PARCELS DISTRICT.

12 Outline of PDD A. General description of the proposed A/R CDM project activity; - Location, Area, plantation models, species, silvi practices.. B. Application of a baseline methodology C. Application of a monitoring methodology and plan D. Estimation the net anthropogenic GHG removals by sinks (Carbon stock benefits) E. Environmental impacts of the proposed A/R CDM project activity F. Socio-economic impacts of the proposed A/R CDM project activity *PDD prepared by team led by Prof. N H Ravinderanath IISCBangalore.

13 Land categories considered.. Degraded forest land Degraded community land Degraded & abandoned private land

14 Model-wise Area 177 Gram Panchayats Land Category Plantation Model Area (ha.) %age Degraded Forest Land Reforestation Degraded Community Land Community forestry Degraded private Land Agro-forestry Total

15 S. No. Scientific Name S. No. Scientific Name S. No. Scientific Name 1 Acacia catechu 16 Gravellia robusta 31 Terminalia arjuna 2 Aegle marmelos 17 Grewia optiva/g. 32 Terminalia chebula oppositifolia 3 Aesculus indica 18 Juglans regia 33 Artocarpus lakoocha 4 Ailanthus altissima/a. 19 Mangifera indica 34 Hicoria carya excelsa 5 Albizzia procera 20 Melia azadirchta 35 Dendrocalamus spps 6 Albizzia lebbek 21 Morus alba 36 Tectona grandis 7 Albizzia stipulata 22 Pinus roxburghii 37 Terminalia tomentosa 8 Alnus nepalensis/a. 23 Pongamia pinnata 38 Prunus armeniaca nitida 9 Azadirachta indica 24 Populus ciliata/p. Alba/P. deltoids 39 Ulmus laevigata/u. wallichiana. 10 Bauhinia variegata 25 Quercus leucotrichophora 40 Prunus cornuta/p. Cerassoides/P.padus 11 Bombax ceiba 26 Robinia 41 Olea glandulifera pseudoacacia 12 Toona ciliata 27 Salix alba 42 Pinus wallichiana 13 Cedrus deodara 28 Sapindus mukorossii 43 Cassia seamia 14 Dalbergia sissoo 29 Syzygium cuminii 44 Acacia nilotica 15 Emblica officinalis 30 Terminalia bellerica 45 Butea monosperma

16 Plantation Strata- 9 Plantation Model Altitude (Mts.) Area (Hectare( Restoration (Degraded Forest Land) Low ( ) Medium ( ) High ( ) Community Forestry (Degraded Community Land) Low ( ) Medium ( ) High ( ) Farm Forestry (Degraded Private & Abandoned Land) Low ( ) Medium ( ) 22.79

17 Project Cycle 10. End of commitment period (2012 / 2017) 9. Certification and Issuance 8. Verification 1. Project identification PIN submission PIN acceptance and fund allocation 2. Carbon asset due diligence New Methodology/ Approved Methodology Project Design Document Monitoring Plan Operational Manual 7. Start of the Project 6. Registration 3. Project due diligence (e.g., environmental and social safeguards) 5. Negotiate Emission Reductions Purchase Agreement (ERPA) 4. Validation (TUV SUD, Germany)

18 Reforestation should lead to increase in Carbon stocks

19 Projected Revenue from Sale of CERs CERs (tco2-e) CERs/year (tco 2 -e) CER revenue (Rs.) at US$ 4.75/tCO 2 Total for the whole project area 8,28,016 41, Average per hectare per year Average INR 2500 per ha per year

20 CARBON REVENUE 10 % Overhead Charges MHWDP/ FOREST DEPARTMENT PRIVATE LAND FOREST LAND COMMUNITY LAND 90 % of carbon revenue Owner or Attorney 20 % of remaining carbon revenue Gram Panchayats GP FUND (undertaking works as approved in GPWDP ) 80 % of remaining carbon revenue USER GROUP/VFDS (members responsible for protection of land parcel) Gram Panchayats GP FUND (undertaking works as approved in GPWDP ) 20 % of carbon revenue 80 % of carbon revenue USER GROUP/VFDS USER GROUPS/ VFDS (members responsible for protection of land parcel depending upon their share /rights in land parcel)

21 Flow of benefits Economic Ecological Socio-Economic NTFPs Watershed protection Involvement of the poorest of poor Fuelwood Biodiversity conservation Capacity building of communities particularly women in management of carbon finance Fodder Soil quality improvement Institutional development Carbon revenue Increased crop productivity

22 Milestones Sept 2006 : PIN Approved May 2008 : PDD Approved : Validation completed June 2011 : Registration ( Effective date March 2011) May 2011 : ERPA signed July 2012 : Carbon Stock Sampling Dec 2012 : Carbon Stock Estimate Oct 2013 : Field Verification done Feb 2014 : Draft Verification Report Ex ante ( ) : tco2 e Actual : tco2 e

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